Improving the Performance of Database Applications by using Black Box Regression Testing

Cluster analysis means placing of the similar set of objects into one form (group) and the dissimilar into another form (group). Where it groups the objects based on the values which will be mentioned at the time of grouping of objects. Clustering is mainly useful for the data summarization and the other purposes. Regression tests, which provides the deviations (differences between two system versions), which may be due to the faults of regression or changes. To analyze the all deviations within the dataset, efficiently it would be difficult to the tester. So placing the similar objects, deviations, meaningful groups of objects that share common characteristics, play an important role in how people analyze and describe the data about the particular cluster. We focus our work on a common type of software system: database applications. Tax Accounting System, Where deviations are dividing objects into groups (clustering) and assigning particular objects to these groups (classification) and also providing the relationship between the clusters and the deviations. Clustering will helps by grouping them, which means each group contain the changes in the particular groups or the another group. Because it is unlikely that analyze which database application has high rate of deviation on year by year so that reason get statistics for future analysis. And computation complexity process is also decreased.